Research questions or hypotheses that seek to explore how an entire social network influences health can assess characteristics of the network's structure in many ways. This section provides examples of instruments used to measure three commonly used characteristics that are discussed in the textbook.

Homogeneity
Density (Typically, size can be assessed using the same measure)
Geographic dispersion

Homogeneity can be measured using items that assess demographic characteristics such as age, race/ethnicity, occupation, or marital status. Instruments may come from a wide range of sources (questionnaires used by the census bureau or other agencies, research studies with similar aims, generated by the researcher)

&ast;Note: Utilizing existing instruments that have been previously tested
is preferable because many psychometric issues must be
considered when creating items.

One way to measure Density is to use a Social Network List (SNL). There has been support for its use in mental health research.

Hirsch (1980)
- Network size assessed by counting the number of significant
others the focal individual lists
- Density is determined from focal individual's judgment of which of
these significant others have relationships with each other

Geographic Dispersion can be measured using a geographic information system (GIS). GIS is a method used to integrate, display and analyze geographic data.

Researchers may also be interested in ways relationships within a social network influence health. This section provides examples of ways two of the more commonly studied characteristics of network relationships have been assessed.

Reciprocity
Emotional Closeness

Reciprocity can be measured several ways. Since reciprocity assesses the benefit from ties within a network, it is closely related to social support and is often determined using social support instruments.

One measure of reciprocity is total reciprocity. Total reciprocity describes whether, on average, relationships within the network give as much support to the focal person as he or she provides to other network members.

- Networks that are not approximately balanced can be described as "underbenefitting" (individual gives more than receives), "overbenefitting" (individual receives more than gives).

- One disadvantage of this approach is the inability to recognize when a network that is reciprocal on average contains many nonreciprocal relationships.

Two alternate approaches address the disadvantage of assessing total reciprocity by examining relationship-specific reciprocity or support-specific reciprocity.

- Relationships-specific: Instead of using a summation of how much support is given and received, assessing reciprocity within specific relationships can identify exactly where "underbenefitting" or"overbenefitting" occurs.

- Support-specific: reciprocity provides more information than total reciprocity by determining the extent to which different types of support may be able to offset one another. For example, provision of a lot of emotional support may not balance the effects of lacking financial assistance.

Source: Tilburg, Sonderen, & Ormel, (1991). The measurement of reciprocity in ego-centered networks of personal relationships: A comparison of various indices. Social Psychology Quarterly, 54(1), 54-66.

Emotional Closeness is typically measured by asking someone to rate their emotional relationship with someone in the network. This can be done using a Likert scale.

For example:
"How would you describe your emotional relationship with your mother/father/closest friend/ main partner at the time of your HIV diagnosis?"
Responses: 1 (very distant) to 4(very close)

Issues that should be considered when measuring features of social networks include:

1. How network ties will be defined. Will only socially recognized roles be included? Only those with whom the focal individual has an emotional bond? Will it be based on the exchange of resources?
2. What is the unit of analysis? A focal individual? Other units, such as families, organizations?

Future direction:
Social networks investigations may benefit from examining other characteristics of social networks, such as directionality, complexity and formality, which have received less attention.